Andre-Tan/2021Dec26-PandasPlotting.ipynb

## 2021Dec26-PandasPlotting.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "da0159a0",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Introduction\" data-toc-modified-id=\"Introduction-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Introduction</a></span></li><li><span><a href=\"#Prepare-Dataset\" data-toc-modified-id=\"Prepare-Dataset-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Prepare Dataset</a></span></li><li><span><a href=\"#Plotting-with-Pandas\" data-toc-modified-id=\"Plotting-with-Pandas-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Plotting with Pandas</a></span></li><li><span><a href=\"#Pandas-Groupby-Plotting\" data-toc-modified-id=\"Pandas-Groupby-Plotting-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Pandas Groupby Plotting</a></span></li><li><span><a href=\"#Creating-Multiple-Plots-in-One-Go\" data-toc-modified-id=\"Creating-Multiple-Plots-in-One-Go-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Creating Multiple Plots in One Go</a></span></li><li><span><a href=\"#Custom-Operations-with-AxesSubplots\" data-toc-modified-id=\"Custom-Operations-with-AxesSubplots-6\"><span class=\"toc-item-num\">6&nbsp;&nbsp;</span>Custom Operations with AxesSubplots</a></span><ul class=\"toc-item\"><li><span><a href=\"#Case-1:-Overlaying-Multiple-Information-in-a-Single-Plot\" data-toc-modified-id=\"Case-1:-Overlaying-Multiple-Information-in-a-Single-Plot-6.1\"><span class=\"toc-item-num\">6.1&nbsp;&nbsp;</span>Case 1: Overlaying Multiple Information in a Single Plot</a></span></li><li><span><a href=\"#Case-2:-Show-Multiple-Information-in-Multiple-Plots,-in-One-Figure\" data-toc-modified-id=\"Case-2:-Show-Multiple-Information-in-Multiple-Plots,-in-One-Figure-6.2\"><span class=\"toc-item-num\">6.2&nbsp;&nbsp;</span>Case 2: Show Multiple Information in Multiple Plots, in One Figure</a></span></li></ul></li><li><span><a href=\"#Pandas-Plotting-Backends\" data-toc-modified-id=\"Pandas-Plotting-Backends-7\"><span class=\"toc-item-num\">7&nbsp;&nbsp;</span>Pandas Plotting Backends</a></span></li><li><span><a href=\"#Ending-Notes\" data-toc-modified-id=\"Ending-Notes-8\"><span class=\"toc-item-num\">8&nbsp;&nbsp;</span>Ending Notes</a></span></li><li><span><a href=\"#References\" data-toc-modified-id=\"References-9\"><span class=\"toc-item-num\">9&nbsp;&nbsp;</span>References</a></span></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "869129e0",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "\n",
    "In my day-to-day job, I work with Pandas to wrangle and extract information from a given dataset. \n",
    "\n",
    "Plotting is an integral part of my job because plots communicate information quickly and easily.\n",
    "\n",
    "**A picture is worth a thousand words**. Is something up? Is something down? Is A and B the same? Rather than looking at a bunch of numbers, you can find patterns in split-second by using plots. \n",
    "\n",
    "See how I use the boring expression at the start of the previous paragraph? Isn't that quicker than me creating a long paragraph stating the exact same thing? I am wasting your time with this paragraph but I want you to see the general idea. This is the same reason why plotting matters. **Plotting gives you the general idea faster**.\n",
    "\n",
    "Stakeholders typically appreciate plots because of the same reason I use it for myself. Everyone's time is saved when you give them plots as a start. When they need to go through the actual numbers, they will ask. \n",
    "\n",
    "---\n",
    "\n",
    "This is a quick go-through of Pandas plotting functions. This article only contains functions I consider to be important in my day-to-day work. \n",
    "\n",
    "If you need more complex/detailed description of the functions, consider going through the actual documentation of the package."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2505b168",
   "metadata": {},
   "source": [
    "# Prepare Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "458b2c1a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T08:25:49.078921Z",
     "start_time": "2022-01-08T08:25:48.002735Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b2d88df9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T08:25:49.828666Z",
     "start_time": "2022-01-08T08:25:49.079915Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17985dca",
   "metadata": {},
   "source": [
    "# Plotting with Pandas\n",
    "\n",
    "Pandas provide a shortcut function to plot data. \n",
    "\n",
    "Let's start with a very bare-bone call to the method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "92b38d72",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T08:25:50.409198Z",
     "start_time": "2022-01-08T08:25:49.875541Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b996070",
   "metadata": {},
   "source": [
    "*Something* come out. It does not explain anything, but it is a start.\n",
    "\n",
    "Let's try to answer something by visualizing it: What is the distribution of `Pclass`?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c6934163",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T08:52:27.656537Z",
     "start_time": "2022-01-08T08:52:27.536165Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the dataset I generated using the chain function above for plotting.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pclass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>491</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pclass\n",
       "1     216\n",
       "2     184\n",
       "3     491"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Titanic Passenger Class Count'}>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = df[\"Pclass\"].value_counts().sort_index().copy()\n",
    "\n",
    "print(\"This is the dataset I generated using the chain function above for plotting.\")\n",
    "display(X.to_frame())\n",
    "\n",
    "X\\\n",
    ".plot(\n",
    "    kind=\"bar\",\n",
    "    grid=True,\n",
    "    legend=True,\n",
    "    title=\"Titanic Passenger Class Count\",\n",
    "    \n",
    "    figsize=(15,5),\n",
    "    xlim=(0,5), ylim=(0,500),\n",
    "    \n",
    "    backend=\"matplotlib\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdd8f3af",
   "metadata": {},
   "source": [
    "Notice that I preprocessed the `pd.DataFrame` before to a `pd.Series` containing the answer to my question.\n",
    "\n",
    "More importantly, notice that I put in a lot of arguments in the plot method now. In the order they are presented as arguments, they are:\n",
    "\n",
    "| Argument | Data Type | Description |\n",
    "| --- | --- | --- |\n",
    "| `kind` | str | The kind of plot to produce. Options are: <br>\\[ `line`, `bar`, `barh`, `hist`, `box`, `kde`, <br>`density`, `area`, `pie`, `scatter`, `hexbin` \\] |\n",
    "| `grid` | bool | Axis grid lines. <br>Notice the light-gray boxes in the second plot? |\n",
    "| `legend` | bool | Place legend on axis subplots |\n",
    "| `title` | str | Title to use for the plot |\n",
    "| `figsize` | tuple | Figure size, (width, height) in inches |\n",
    "| `xlim` | tuple | Set x-limits of the current axes |\n",
    "| `ylim` | tuple | Set y-limits of the current axes |\n",
    "| `backend` | str | Which plotting backend to use. Go to [Pandas Plotting Backend](#Bonus:-Pandas-Plotting-Backends)\n",
    "\n",
    "Notice also that the bare-bone call to the method returns a plot. Matplotlib (and thus Pandas) has default values for all the arguments, so you may not need to know and understand every arguments out there.\n",
    "\n",
    "All the available arguments in detail can be read in [Pandas `plot` Documentation](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.html).\n",
    "\n",
    "Generally speaking, the arguments I listed above are the ones I use on a day-to-day basis. There are also some I use depending on the `kind` of the plot, which I will show in later sections."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6ff7c23",
   "metadata": {},
   "source": [
    "# Pandas Groupby Plotting\n",
    "\n",
    "Pandas plotting does not understand multi-index easily. Always use single-index as it is the one that will be used as X-axis. \n",
    "\n",
    "The function `unstack` or `melt` may help a lot here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "f28a74bc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T10:28:50.665815Z",
     "start_time": "2022-01-08T10:28:50.504529Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the dataset I generated using the chain function above for plotting.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sex</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(0.419, 19.0]</th>\n",
       "      <td>0.706667</td>\n",
       "      <td>0.292135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(19.0, 25.0]</th>\n",
       "      <td>0.723404</td>\n",
       "      <td>0.122222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(25.0, 31.8]</th>\n",
       "      <td>0.727273</td>\n",
       "      <td>0.216867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(31.8, 41.0]</th>\n",
       "      <td>0.843137</td>\n",
       "      <td>0.215054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(41.0, 80.0]</th>\n",
       "      <td>0.795455</td>\n",
       "      <td>0.183673</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sex              female      male\n",
       "Age                              \n",
       "(0.419, 19.0]  0.706667  0.292135\n",
       "(19.0, 25.0]   0.723404  0.122222\n",
       "(25.0, 31.8]   0.727273  0.216867\n",
       "(31.8, 41.0]   0.843137  0.215054\n",
       "(41.0, 80.0]   0.795455  0.183673"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Age'>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kwargs = {\n",
    "    \"grid\": True,\n",
    "    \"figsize\": (12, 6),\n",
    "    \"style\": \"o-\",\n",
    "}\n",
    "\n",
    "X = df.groupby([\n",
    "    \"Sex\", pd.qcut(df[\"Age\"], q=5, duplicates=\"drop\")\n",
    "])[\"Survived\"].mean().unstack(level=0)\n",
    "\n",
    "print(\"This is the dataset I generated using the chain function above for plotting.\")\n",
    "display(X)\n",
    "\n",
    "X.plot(**kwargs, kind=\"line\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7eb272a",
   "metadata": {},
   "source": [
    "# Creating Multiple Plots in One Go\n",
    "\n",
    "Pandas has a shortcut argument to create multiple plots in a single Pandas command with `subplots=True`. It plots each column into single plot. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "61fa8110",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T08:54:18.618348Z",
     "start_time": "2022-01-08T08:54:18.385448Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the dataset I generated using the chain function above for plotting.\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sex</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(0.419, 19.0]</th>\n",
       "      <td>0.706667</td>\n",
       "      <td>0.292135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(19.0, 25.0]</th>\n",
       "      <td>0.723404</td>\n",
       "      <td>0.122222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(25.0, 31.8]</th>\n",
       "      <td>0.727273</td>\n",
       "      <td>0.216867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(31.8, 41.0]</th>\n",
       "      <td>0.843137</td>\n",
       "      <td>0.215054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(41.0, 80.0]</th>\n",
       "      <td>0.795455</td>\n",
       "      <td>0.183673</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sex              female      male\n",
       "Age                              \n",
       "(0.419, 19.0]  0.706667  0.292135\n",
       "(19.0, 25.0]   0.723404  0.122222\n",
       "(25.0, 31.8]   0.727273  0.216867\n",
       "(31.8, 41.0]   0.843137  0.215054\n",
       "(41.0, 80.0]   0.795455  0.183673"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'female'}, xlabel='Age'>,\n",
       "        <AxesSubplot:title={'center':'male'}, xlabel='Age'>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = df.groupby([\n",
    "    df[\"Sex\"],\n",
    "    pd.qcut(df[\"Age\"], q=5, duplicates=\"drop\")\n",
    "])[\"Survived\"].mean().unstack(level=0)\n",
    "\n",
    "print(\"This is the dataset I generated using the chain function above for plotting.\")\n",
    "display(X)\n",
    "\n",
    "X.plot(\n",
    "    kind=\"bar\", \n",
    "    grid=True,\n",
    "    legend=False,\n",
    "    title=\"Survival Rate Grouped by Age Range and Gender\",\n",
    "    \n",
    "    figsize=(15,5), \n",
    "\n",
    "    subplots=True, layout=(1,2),\n",
    "    sharex=True, sharey=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb22e3af",
   "metadata": {},
   "source": [
    "In my sample `pd.DataFrame` above, I have 2 columns: `male` and `female`. Adding `subplots=True` plots the 2 columns into 2 separate plots.\n",
    "\n",
    "Some new arguments shown in this section:\n",
    "\n",
    "| Argument | Data Type | Description |\n",
    "| --- | --- | --- |\n",
    "| `subplots` | bool | Make separate subplots for each column |\n",
    "| `layout` | tuple | (rows, columns) for the layout of subplots. <br>In my example, I choose subplots of 1 row and 2 columns. |\n",
    "| `sharex` | bool | Shortcut to set the same `xlim` for all plot in subplots |\n",
    "| `sharey` | bool | Shortcut to set the same `ylim` for all plot in subplots |\n",
    "\n",
    "This [Pandas `subplot` Documentation](https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html#subplots) might be useful.\n",
    "\n",
    "---\n",
    "\n",
    "# Custom Operations with AxesSubplots\n",
    "\n",
    "Notice something here. In the section [Plotting with Pandas](http://localhost:8888/notebooks/PycharmProjects/ScratchPads/2021Dec26%20-%20Matplotlib%20Tutorial.ipynb#Plotting-with-Pandas), the output returned by Pandas is:\n",
    "\n",
    "```\n",
    "<AxesSubplot:title={'center':'Titanic Passenger Class Count'}>\n",
    "```\n",
    "\n",
    "While now it is:\n",
    "\n",
    "```\n",
    "array([[<AxesSubplot:title={'center':'female'}, xlabel='Age'>,\n",
    "        <AxesSubplot:title={'center':'male'}, xlabel='Age'>]],\n",
    "      dtype=object)\n",
    "```\n",
    "\n",
    "The argument `subplots=True` returns the same object as when you ask for a single plot: `AxesSubplot`. The difference is that now it is a list/array of `AxesSubplot`.\n",
    "\n",
    "To understand why this matters, you need to know a bit about Matplotlib class of `Figure` and `AxesSubplot`. \n",
    "\n",
    "Check out this Matplotlib helper function to create subplots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c7010679",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T09:13:35.040863Z",
     "start_time": "2022-01-08T09:13:34.846874Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 1080x360 with 2 Axes>,\n",
       " array([<AxesSubplot:>, <AxesSubplot:>], dtype=object))"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(\n",
    "    nrows=1, ncols=2,\n",
    "    figsize=(15, 5),\n",
    "    tight_layout=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98154bea",
   "metadata": {},
   "source": [
    "The function returns a tuple of (`Figure`, array(\\[`AxesSubplot`\\])). \n",
    "\n",
    "Think of `Figure` as the frame containing single/multiple `AxesSubplot`. I generally do not process `Figure` much, but care a whole deal with the array of `AxesSubplot`. \n",
    "\n",
    "What Pandas does with the argument `subplots=True` is create a tuple of (`Figure`, array(\\[`AxesSubplot`\\])), and send the intended data to be visualized into specified `AxesSubplot`. This link to a [TowardsDataScience article](https://towardsdatascience.com/clearing-the-confusion-once-and-for-all-fig-ax-plt-subplots-b122bb7783ca)  explains it in more detail.\n",
    "\n",
    "Let me try making the exact same subplots without Pandas shortcut function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "28478db2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T09:35:21.232056Z",
     "start_time": "2022-01-08T09:35:21.015482Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the dataset I generated using the chain function above for plotting.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sex</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(0.419, 19.0]</th>\n",
       "      <td>0.706667</td>\n",
       "      <td>0.292135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(19.0, 25.0]</th>\n",
       "      <td>0.723404</td>\n",
       "      <td>0.122222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(25.0, 31.8]</th>\n",
       "      <td>0.727273</td>\n",
       "      <td>0.216867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(31.8, 41.0]</th>\n",
       "      <td>0.843137</td>\n",
       "      <td>0.215054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(41.0, 80.0]</th>\n",
       "      <td>0.795455</td>\n",
       "      <td>0.183673</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sex              female      male\n",
       "Age                              \n",
       "(0.419, 19.0]  0.706667  0.292135\n",
       "(19.0, 25.0]   0.723404  0.122222\n",
       "(25.0, 31.8]   0.727273  0.216867\n",
       "(31.8, 41.0]   0.843137  0.215054\n",
       "(41.0, 80.0]   0.795455  0.183673"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'male'}, xlabel='Age'>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = df.groupby([\n",
    "    df[\"Sex\"],\n",
    "    pd.qcut(df[\"Age\"], q=5, duplicates=\"drop\")\n",
    "])[\"Survived\"].mean().unstack(level=0)\n",
    "\n",
    "print(\"This is the dataset I generated using the chain function above for plotting.\")\n",
    "display(X)\n",
    "\n",
    "fig, axes = plt.subplots(\n",
    "    nrows=1, ncols=2, \n",
    "    figsize=(15,5),\n",
    "    sharey=True\n",
    ")\n",
    "fig.suptitle(\"Survival Rate Grouped by Age Range and Gender\")\n",
    "\n",
    "X[\"female\"].plot(\n",
    "    kind=\"bar\",\n",
    "    grid=True,\n",
    "    legend=False,\n",
    "    title=\"female\",\n",
    "    \n",
    "    ax=axes[0]\n",
    ")\n",
    "\n",
    "X[\"male\"].plot(\n",
    "    kind=\"bar\",\n",
    "    grid=True,\n",
    "    legend=False,\n",
    "    title=\"male\",\n",
    "    color=\"orange\",\n",
    "    ax=axes[1]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1885c07b",
   "metadata": {},
   "source": [
    "The color for the male gender is slightly off, but it gives us the same plots as the previous section. The big things to notice:\n",
    "\n",
    "1. There is a variable `suptitle` in the `Figure` object which gives me the title over both plots.\n",
    "2. When I plot single `pd.Series` once each for female and male gender, I pass over an argument `ax`.\n",
    "\n",
    "Point 2 is important here. Pandas by default creates a new `AxesSubplot` when you do not supply the argument `ax`. This means different `AxesSubplot` for every plot created. \n",
    "\n",
    "When you do supply the argument `ax`, Pandas will direct the created plot to said `ax`. You can design however you want a plot/subplots to look like!\n",
    "\n",
    "Here are 2 cases I generally find I want to do."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff99dbbb",
   "metadata": {},
   "source": [
    "## Case 1: Overlaying Multiple Information in a Single Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "b1515d14",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T09:48:34.442371Z",
     "start_time": "2022-01-08T09:48:34.319711Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A helper function to create an ax\n",
    "# ax = plt.subplot(111)\n",
    "\n",
    "# You can also use plt.subplots without nrow and ncol argument\n",
    "fig, ax = plt.subplots(\n",
    "    figsize=(15,5)\n",
    ")\n",
    "\n",
    "X[\"female\"].plot(\n",
    "    kind=\"bar\",\n",
    "    ax=ax\n",
    ")\n",
    "\n",
    "X[\"male\"].plot(\n",
    "    kind=\"line\",\n",
    "    style=\"ro-\",\n",
    "    linewidth=3,\n",
    "    ax=ax\n",
    ")\n",
    "\n",
    "# Notice that you can set AxesSubplot variables easily this way\n",
    "ax.set_title(\"Female Survival Rate (Bar) Overlaid by Male Survival Rate (Line)\")\n",
    "ax.set_ylim([0, 1])\n",
    "ax.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a028a8ea",
   "metadata": {},
   "source": [
    "## Case 2: Show Multiple Information in Multiple Plots, in One Figure\n",
    "\n",
    "Using the information from the leading section, let me show all kind of plots you can create with Matplotlib on Pandas.\n",
    "\n",
    "I will use this example to show all Matplotlib Plot `kind` you can create in Pandas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "7ef1eac4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-08T10:35:32.023384Z",
     "start_time": "2022-01-08T10:35:30.357602Z"
    },
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Hexbin Plot - Titanic Age Distribution by Fare'}, xlabel='Age', ylabel='Fare'>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1800 with 11 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def generate_subplot_tuple(nrows, ncols, figsize_each):\n",
    "    fig, axes = plt.subplots(\n",
    "        nrows=nrows, ncols=ncols, \n",
    "        figsize=(figsize_each[0]*ncols, figsize_each[1]*nrows),\n",
    "        tight_layout=True\n",
    "    )\n",
    "    return fig, axes\n",
    "\n",
    "fig, (\n",
    "    (ax1, ax2), (ax3, ax4), (ax5, ax6), (ax7, ax8), (ax9, ax10)\n",
    ") = generate_subplot_tuple(nrows=5, ncols=2, figsize_each=(8, 5))\n",
    "\n",
    "axes = axes.flatten()\n",
    "\n",
    "X = df[[\"Age\", \"Survived\"]].copy()\n",
    "X = X.groupby([pd.qcut(X[\"Age\"], q=10, duplicates=\"drop\")])\\\n",
    "[\"Survived\"].agg([\"count\", \"sum\", \"mean\"])\n",
    "\n",
    "X[\"mean\"].plot(\n",
    "    kind=\"line\", style=\"o-\",\n",
    "    grid=True, ylim=(0,1), \n",
    "    ax=ax1, title=\"Line Plot - Titanic Survival Based on Age Intervals\",\n",
    ")\n",
    "X[\"mean\"].plot(\n",
    "    kind=\"bar\",\n",
    "    grid=True, ylim=(0,1),\n",
    "    ax=ax2, title=\"Bar Plot - Titanic Survival Based on Age Intervals\",\n",
    ")\n",
    "X[\"mean\"].plot(\n",
    "    kind=\"barh\",\n",
    "    grid=True, ylim=(0,1),\n",
    "    ax=ax3, title=\"Barh Plot - Titanic Survival Based on Age Intervals\",\n",
    ")\n",
    "\n",
    "X = df[[\"PassengerId\", \"Age\", \"Fare\"]].copy()\n",
    "\n",
    "X.plot(\n",
    "    kind=\"box\",\n",
    "    grid=True, legend=True,\n",
    "    ax=ax4, title=\"Boxplot - Titanic Survival Based on Age Intervals\",\n",
    ")\n",
    "\n",
    "X = df[[\"Age\", \"Sex\", \"Pclass\", \"Embarked\", \"Survived\"]].copy()\n",
    "\n",
    "X.groupby([\"Sex\"])[\"Age\"].plot(\n",
    "    kind=\"hist\", bins=50, alpha=0.6, density=True, \n",
    "    # False=Count, True=Frequency\n",
    "    grid=True, legend=True,\n",
    "    ax=ax5, title=\"Histogram - Titanic Passenger Age Distribution by Gender\",  \n",
    ")\n",
    "\n",
    "X.groupby([\"Sex\"])[\"Age\"].plot(\n",
    "    kind=\"kde\",\n",
    "    grid=True, legend=True,\n",
    "    ax=ax6, title=\"KDE/Density Plot - Titanic Passenger Age Distribution by Gender\",\n",
    ")\n",
    "\n",
    "X = df[[\"Pclass\", \"Embarked\", \"PassengerId\", \"Age\", \"Fare\", \"Sex\"]].copy()\n",
    "\n",
    "X.groupby([\"Pclass\", \"Embarked\"]).size().unstack(level=0).plot(\n",
    "    kind=\"area\", stacked=True,\n",
    "    grid=True, legend=True,\n",
    "    ax=ax7, title=\"Area Plot - Titanic PClass Distribution by Embark\",\n",
    ")\n",
    "\n",
    "X.groupby([\"Pclass\"])[\"Sex\"].value_counts().plot(\n",
    "    kind=\"pie\",\n",
    "    grid=True, legend=True,\n",
    "    ax=ax8, title=\"Area Plot - Titanic PClass Distribution by Embark\",\n",
    ")\n",
    "\n",
    "X.plot(\n",
    "    kind=\"scatter\",\n",
    "    x=\"Age\", y=\"Fare\",\n",
    "    grid=True, legend=True,\n",
    "    ax=ax9, title=\"Area Plot - Titanic PClass Distribution by Embark\",\n",
    ")\n",
    "\n",
    "X[X[\"Fare\"]<200].plot(\n",
    "    kind=\"hexbin\", gridsize=20, bins=20,\n",
    "    x=\"Age\", y=\"Fare\",\n",
    "    grid=True, legend=True,\n",
    "    ax=ax10, title=\"Hexbin Plot - Titanic Age Distribution by Fare\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f0fdcab",
   "metadata": {},
   "source": [
    "# Pandas Plotting Backends\n",
    "\n",
    "By default, Pandas `plot` will return a Matplotlib plot. You can however change the backend used for plotting **while keeping majority of the same plotting syntax you are used to**. \n",
    "\n",
    "List of supported Plotting Backends are listed in [this page](https://pandas.pydata.org/pandas-docs/dev/ecosystem.html#visualization).\n",
    "\n",
    "I use Plotly for better visualization and real-time hover capability. To use it with Pandas, I have historically been using a third-party package called [Cufflinks](https://github.com/santosjorge/cufflinks). \n",
    "\n",
    "I am currently trying to move to using Plotly directly with Pandas to lower the number of dependencies involved.\n",
    "\n",
    "```\n",
    "# You can set the plotting backend for every pandas plot.\n",
    "pd.options.plotting.backend = \"plotly\" # Default: \"matplotlib\"\n",
    "\n",
    "# Or, customize the backend for any plot.\n",
    "df.plot(backend=\"plotly\")\n",
    "```\n",
    "\n",
    "# Ending Notes\n",
    "\n",
    "Generally all simple plots can be made with shortcuts already provided by Pandas (and its plotting backends). You just need to arrange your data to follow what is expected by Pandas for it to produce the plots.\n",
    "\n",
    "When you need to do more difficult visualization, it never hurts to read the documentation and example code of the plotters, such as one here for [Matplotlib Tutorials](https://matplotlib.org/stable/tutorials/index.html)."
   ]
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    "# References\n",
    "\n",
    "\n",
    "1. [Pandas Plot Documentation](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.html)\n",
    "2. [Chart Visualization (contains info about subplots + other useful info)](https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html#)\n",
    "3. [Matplotlib Figure, AxesSubplot in Detail](https://towardsdatascience.com/clearing-the-confusion-once-and-for-all-fig-ax-plt-subplots-b122bb7783ca)\n",
    "4. [Pandas Plotting Backend](https://pandas.pydata.org/pandas-docs/dev/ecosystem.html#visualization)\n",
    "5. [Matplotlib Tutorials](https://matplotlib.org/stable/tutorials/index.html)"
   ]
  }
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